The global clustering of inventive talent shapes innovation capacity and drives economic growth.For China,this process is especially crucial in sustaining its development momentum.This paper draws on data from the EPO...The global clustering of inventive talent shapes innovation capacity and drives economic growth.For China,this process is especially crucial in sustaining its development momentum.This paper draws on data from the EPO Worldwide Patent Statistical Database(PATSTAT)to extract global inventive talent mobility information and analyzes the spatial structural evolution of the global inventive talent flow network.The study finds that this network is undergoing a multi-polar transformation,characterized by the rising importance of a few central countries-such as the United States,Germany,and China-and the increasing marginalization of many peripheral countries.In response to this typical phenomenon,the paper constructs an endogenous migration model and conducts empirical testing using the Temporal Exponential Random Graph Model(TERGM).The results reveal several endogenous mechanisms driving global inventive talent flows,including reciprocity,path dependence,convergence effects,transitivity,and cyclic structures,all of which contribute to the network’s multi-polar trend.In addition,differences in regional industrial structures significantly influence talent mobility choices and are a decisive factor in the formation of poles within the multi-polar landscape.Based on these findings,it is suggested that efforts be made to foster two-way channels for talent exchange between China and other global innovation hubs,in order to enhance international collaboration and knowledge flow.We should aim to reduce the migration costs and institutional barriers faced by R&D personnel,thereby encouraging greater mobility of high-skilled talent.Furthermore,the government is advised to strategically leverage regional strengths in high-tech industries as a lever to capture competitive advantages in emerging technologies and products,ultimately strengthening the country’s position in the global innovation landscape.展开更多
Theoretic and practical significance has been highlighted in the research of the roles and functions of destinations,as destinations are restricted by the spatial structure based on tourist flow network from the persp...Theoretic and practical significance has been highlighted in the research of the roles and functions of destinations,as destinations are restricted by the spatial structure based on tourist flow network from the perspective of relationship.This article conducted an empirical analysis for Tourism Region of South Anhui(TRSA) and revealed the necessity and feasibility of studying the roles and functions of destinations from tourist flow network's perspective.The automorphic equivalence analysis and centrality analysis were used to classify 16 destinations in TRSA into six role types:tourist flow distribution center,hub of tourist flows,passageway destination,common touring destination,attached touring destination,and nearly isolated destination.Some suggestions were given on suitable infrastructure construction and destinations service designs according to their functions in network.This destination role positioning was based on tourist flow network structure in integral and macroscopic way.It provided an important reference for the balanced and harmonious development of all the destinations of TRSA.In addition,this article verified the applicability of social network analysis on tourist flow research in local scale,and expanded this method to destination role and function positioning.展开更多
Computer networks and power transmission networks are treated as capacitated flow networks.A capacitated flow network may partially fail due to maintenance.Therefore,the capacity of each edge should be optimally assig...Computer networks and power transmission networks are treated as capacitated flow networks.A capacitated flow network may partially fail due to maintenance.Therefore,the capacity of each edge should be optimally assigned to face critical situations-i.e.,to keep the network functioning normally in the case of failure at one or more edges.The robust design problem(RDP)in a capacitated flow network is to search for the minimum capacity assignment of each edge such that the network still survived even under the edge’s failure.The RDP is known as NP-hard.Thus,capacity assignment problem subject to system reliability and total capacity constraints is studied in this paper.The problem is formulated mathematically,and a genetic algorithm is proposed to determine the optimal solution.The optimal solution found by the proposed algorithm is characterized by maximum reliability and minimum total capacity.Some numerical examples are presented to illustrate the efficiency of the proposed approach.展开更多
In a large area of the east—central Asian continent there is a unified seismic network system composed of two families of large—seismic belts that intersect conjugately. Such a seismic network in the middle—upper c...In a large area of the east—central Asian continent there is a unified seismic network system composed of two families of large—seismic belts that intersect conjugately. Such a seismic network in the middle—upper crust is actually a response to the plastic flow network in the lower lithosphere including the lower crust and lithospheric mantle. The existence of the unified plastic flow system confirms that the driving force for intraplate tectonic deformation results mainly from the compression of the India plate, while the long-range transmission of the force is carried out chiefly by means of plastic flow. The plastic flow network has a control over the intraplate tectonic deformation.展开更多
Based on the heat flow data published in 1990 and 2001, a study of the factors influencing the terrestrial heat flow distribution in the China continent and its quantitative expression is carried out using the ＂Netli...Based on the heat flow data published in 1990 and 2001, a study of the factors influencing the terrestrial heat flow distribution in the China continent and its quantitative expression is carried out using the ＂Netlike Plastic-Flow＂ continental dynamics model and the methods of statistic analysis and optimum fitting. The result indicates that the factors influencing the heat flow distribution is classified into two groups, i.e. background and tectonic ones, in which the former mainly involves the non- uniform distribution of mantle heat flow, heat production of radioactive dements in the crust, heattransfer media and hydrothermal circulation, while the latter mainly involves plastic-flow networks and relatively-stable blocks. The plastic-flow network is a manifestation of shear localization in the netlike plastic-flow process in the lower lithosphere, which is composed of two sets of plastic-flow belts （PFBs） intersecting each other and, as one of the basic action regimes, controls the intraplate tectonic deformation. Relatively stable blocks （RSBs）, which are the tectonic units with relatively-high viscosities existing in the netlike plastic-flow field, as one of the principal origins, result in the development of large-seale compressional basins. PFB and RSB, as the active and quiet states of tectonic deformation, give rise to the higher and lower heat flow values, respectivdy. The provincial average heat flow in continent can be estimated using the expression qav = q0 ＋ a Pbt-c Pbk, where the three terms of the right side are background heat flow, PFB-positive contribution and RSB-negative contribution, Pbt and Pbk are the PFB- and RSB-coverage ratios, respectively, a is the coefficient of PFB- positive contribution depending mainly on the strain in the lower lithosphere, and c is the coefficient of RSB-negative contribution related mainly to the thickness of the lithosphere, the aseismic-area ratio and the tectonic age. For the major portion of the China continent excluding some of the southeastern region of China, the confidence interval of the provincial average background heat flow is qo=57.25±24.8 mW/m^2 and the PFB-positive- and RSB-negative-contribution coefficients are a=14.8-71.9 mW/m^2 and c=0-25.6 mW/m^2, respectively. The concepts of PFB and RSB effects and the heat flow expression suggested provide a new choice of the approach to the quantitative description of the characteristics of heat flow distribution in continent and their physical mechanisms.展开更多
Multipe NSSS (Nuclear Steam Supply System) modules use the common feeding-water system to drive the common turbine power generation set. The SSFFN (secondary side fluid flow network) of MHTGR plant has features i.e. s...Multipe NSSS (Nuclear Steam Supply System) modules use the common feeding-water system to drive the common turbine power generation set. The SSFFN (secondary side fluid flow network) of MHTGR plant has features i.e. strong-coupling and nonlinearity. A wide range of power switching operation will cause unsteady flow, which may destroy the working elements and will be a threat for normal operation. To overcome those problems, a differential-algebraic model and PI controllers are designed for the SSFFN. In MATLAB\SIMULINK environment, a simulation platform is established and used to make a simulation of SSFFN of a MHTGR plant with two NSSS modules, which uses feedwater valves to control the mass flow rate in each module instead of feedwater pump. Results reflect good robustness of controllers.展开更多
Several conclusions on minimal cutset are proposed, from which a new algorithm is deduced to evaluate the unreliability of flow networks. Beginning with one unreliability product of the network, disjointed unreliabili...Several conclusions on minimal cutset are proposed, from which a new algorithm is deduced to evaluate the unreliability of flow networks. Beginning with one unreliability product of the network, disjointed unreliability products are branched out one by one, every of which is selected from the network minimal cutsets. Finally the unreliability of the network is obtained by adding all these unreliability products up.展开更多
Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose...Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks.Design/Methodology/Approach:The IKM model enhances the preferential attachment and growth observed in scale-free BA networks,while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network.To compare its performance,the BA and DMS models are also employed for simulating the network.Pearson coefficient analysis is conducted on the simulated networks generated by the IKM,BA and DMS models,as well as on the actual network.Findings:The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network.It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm.The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units.Research Limitations:This study has some limitations.Firstly,it primarily focuses on the evolution of knowledge flow networks within the field of physics,neglecting other fields.Additionally,the analysis is based on a specific set of data,which may limit the generalizability of the findings.Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets.Practical Implications:The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions.It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations.The model can aid in optimizing knowledge flow and enhancing collaboration within organizations.Originality/value:This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks.The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions.Moreover,the model has the potential to be applied to other knowledge networks,which are formed by knowledge organizations as node units.展开更多
In the present paper, a three-component, stationary, multistate flow network system is studied. Detailed costs and incomes are specified. The aim is to minimize the expected total net loss with respect to the expected...In the present paper, a three-component, stationary, multistate flow network system is studied. Detailed costs and incomes are specified. The aim is to minimize the expected total net loss with respect to the expected times the components spend in each state. This represents a novelty in that we connect the expected component times spent in each state to the minimal total net loss of the system, without first finding the component importance. This is of interest in the design phase where one may tune the components to minimize the expected total net loss. Due to the complex nature of the problem, we first study a simplified version. There the expected times spent in each state are assumed equal for each component. Then a modified version of the full model is presented. The optimization in this model is completed in two steps. First the optimization is carried out for a set of pre-chosen fixed expected life cycle lengths. Then the overall minimum is identified by varying these expectations. Both the simplified and the modified optimization problems are nonlinear. The setup used in this article is such that it can easily be modified to represent other flow network systems and cost functions. The challenge lies in the optimization of real life systems.展开更多
The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology.Image semantic segmentation can help the unmanned driving sy...The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology.Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis.Semantic segmentation is also a challenging technology for image understanding and scene parsing.We focused on the challenging task of real-time semantic segmentation in this paper.In this paper,we proposed a novel fast architecture for real-time semantic segmentation named DuFNet.Starting from the existing work of Bilateral Segmentation Network(BiSeNet),DuFNet proposes a novel Semantic Information Flow(SIF)structure for context information and a novel Fringe Information Flow(FIF)structure for spatial information.We also proposed two kinds of SIF with cascaded and paralleled structures,respectively.The SIF encodes the input stage by stage in the ResNet18 backbone and provides context information for the feature fusionmodule.Features from previous stages usually contain rich low-level details but high-level semantics for later stages.Themultiple convolutions embed in Parallel SIF aggregate the corresponding features among different stages and generate a powerful global context representation with less computational cost.The FIF consists of a pooling layer and an upsampling operator followed by projection convolution layer.The concise component provides more spatial details for the network.Compared with BiSeNet,our work achieved faster speed and comparable performance with 72.34%mIoU accuracy and 78 FPS on Cityscapes Dataset based on the ResNet18 backbone.展开更多
To clarify fluid flow mechanisms and establish effective development conditions in continental shale oil reservoirs,a high-temperature,high-pressure steady-state flow system integrated with nuclear magnetic resonance(...To clarify fluid flow mechanisms and establish effective development conditions in continental shale oil reservoirs,a high-temperature,high-pressure steady-state flow system integrated with nuclear magnetic resonance(NMR)technology has been developed.The apparatus combines sample evacuation,rapid pressurization and saturation,and controlled displacement,enabling systematic investigation of single-phase shale oil flow under representative reservoir conditions.Related experiments allow proper quantification of the activation thresholds and relative contributions of different pore types to flow.A movable fluid index(MFI),defined using dual T_(2) cutoff values,is introduced accordingly and linked to key flow parameters.The results reveal distinct multi-scale characteristics of single-phase shale oil transport,namely micro-scale graded displacement and macro-scale segmented nonlinear behavior.As the injection-production pressure difference increases,flow pathways are activated progressively,beginning with fractures,followed by large and then smaller macropores,leading to a pronounced enhancement in apparent permeability.Although mesopores and micropores contribute little to direct flow,their indirect influence becomes increasingly important,and apparent permeability gradually approaches a stable limit at higher pressure difference.It is also shown that the MFI exhibits a strong negative correlation with the starting pressure gradient and a positive correlation with apparent permeability,providing a rapid and reliable indicator of shale oil flow capacity.Samples containing through-going fractures display consistently higher MFI values and superior flowability compared with those dominated by laminated fractures,highlighting the pivotal role of well-connected fracture networks generated by large-scale hydraulic fracturing in improving shale oil production.展开更多
This study investigates the enhancement of convective heat transfer in a serpentine pipe using ferrofluid flow influenced by dual non-uniform magnetic sources.The primary objective is to improve thermal performance in...This study investigates the enhancement of convective heat transfer in a serpentine pipe using ferrofluid flow influenced by dual non-uniform magnetic sources.The primary objective is to improve thermal performance in compact cooling systems,such as those used in heat exchangers.A two-dimensional,steady-state Computational Fluid Dynamic(CFD)model is developed in ANSYS Fluent to simulate the behavior of an incompressible ferrofluid under applied constant heat flux and magnetic fields.The magnetic force is modeled using the Kelvin force,which acts on magnetized nanoparticles in response to spatially varying electromagnetic fields generated by two strategically positioned current-carrying wires.The effects of magnetic field strength,quantified by the magnetic number(Mn),on flow behavior and temperature distribution are thoroughly analyzed.The results indicate that increasing Mn leads to higher Nusselt numbers,demonstrating enhanced convective heat transfer.Secondary vortices induced by magnetic forcing improve fluid mixing,particularly in curved regions of the pipe.A mesh-independence study and model validation with benchmark data support the reliability of the numerical framework.This work highlights the potential of magnetic-field-assisted thermal control in energy-efficient cooling applications and provides a foundation for the further development of advanced ferrofluid-based heat transfer systems.展开更多
The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a wat...The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates.This problem is important because it helps us understand the complicated connections between magnetic fields,nanofluid dynamics,and heat transport,all of which are critical for designing thermal management systems.These findings are especially useful for improving the design of innovative cooling technologies in electronics,energy systems,and healthcare applications.No prior study has been done on the theoretical study of the flow of ternary nanofluid(SiO_(2)+ZnO+MWCNT/Water−EthylGl ycol,(60∶40))past a pierced squeezed Riga plates using the boundary value problem solver 4th-order collocation(BVP4C)numerical approach to date.So,the current work has been carried out to fill this gap,and the core purpose of this study is to explore the aspects that enhance the heat transfer of base fluids(H_(2)O/EG)suspended with three nanomaterials SiO_(2),ZnO,and MWCNT.The Riga plates introduce electromagnetic forcing through an embedded array of magnets and electrodes,generating Lorentz forces to regulate the flow.The squeezing effect introduces dynamic boundary movement,which enhances mixing;however,permeability,due to porosity,replicates the true material limits.Similarity transformations of the Navier-Stokes and energy equations result in a highly nonlinear set of ordinary differential equations that govern momentum and thermal energy transport.The subsequent boundary value problem is solved utilizing the BVP4C numerical approach.The study observes the impact of magnetic parameters,squeezing velocity,solid volume percentages of the three nanoparticles,and porous medium factors on velocity and temperature fields.Results show that magnetic fields reduce the velocity profile by 6.75%due to increased squeezing and medium effects.Tri-hybrid nanofluids notice a 9%rise in temperature with higher thermal radiation.展开更多
The escalating ecological consequences of state transitions have attracted significant attention in both theoretical and experimental studies,with a focus on determining the stable or equilibrium points of dynamic sys...The escalating ecological consequences of state transitions have attracted significant attention in both theoretical and experimental studies,with a focus on determining the stable or equilibrium points of dynamic systems[1-5].Identifying equilibrium states not only reveals a system's current status but also offers insights into its evolutionary trajectory under specific environmental conditions[6].展开更多
Taking Shanghai as an example,this study obtained the online travel notes data from Xiaohongshu and Qunar in the past 10 years to construct the Shanghai tourist flow network(STFN)and used the methods of change point d...Taking Shanghai as an example,this study obtained the online travel notes data from Xiaohongshu and Qunar in the past 10 years to construct the Shanghai tourist flow network(STFN)and used the methods of change point detection(CPD)and complex network analysis(CNA)to reveal the spatial structure characteristics of Shanghai tourism flow and the dynamic evolution process of STFN.The results showed that:(1)In the past 10 years,Shanghai tourist market had experienced a process of evolution from stable and orderly to short-term fluc-tuation and then gradual recovery,and the year of 2019 was the turning point of tourist flow network evolution.(2)The small-world and approximate scale-free characteristics of STFN were verified,and the network changed from disassortative to temporary assortative,showing a development trend of external expansion and internal separation.(3)While the centrality indicators of tourist flow network remained stable as a whole,the attention to cultural nodes was also increasing with the emergence of new nodes;(4)In terms of spatial connection,new popular nodes emerged and the relationship between them and the surrounding nodes was strengthened;(5)The spatial pattern of tourist flow network presented an inverted“V”shape and gradually expanded to southwest and southeast,forming a network with core nodes as the center and radiating outward.At the same time,newly emerging nodes at the periphery had formed relatively independent clusters.展开更多
Hilly terrain pipeline is a common form of pipeline in oil and gas storage and transportation industry.Due to the hilly terrain influence, the liquid at the elbow of the gathering pipeline is easy to flow back and acc...Hilly terrain pipeline is a common form of pipeline in oil and gas storage and transportation industry.Due to the hilly terrain influence, the liquid at the elbow of the gathering pipeline is easy to flow back and accumulate to form slug flow, so it is necessary to remove the accumulated liquid by gas purging. In this paper, experiment is carried out in hilly terrain pipelines. Three flow patterns of stratified flow, slug flow and stratified entrained flow are observed. The process of gas purging accumulated liquid is divided into four stages, namely liquid accumulation, liquid rising, continuous outflow and tail outflow. At the same time, the flow pattern maps of each stage are drawn. The pressure drop signal is analyzed in time domain and frequency domain, and the contour map of pressure drop distribution is drawn. It is found that the ratio of range to average value can well distinguish the occurrence range of each flow pattern.Based on visualization, the transition process of slug flow to stratified flow and stratified entrained flow is studied, and the transition boundary prediction model is established. An image processing method is proposed to convert the image signal into a similarity curve, and PSD analysis is performed to calculate the slug frequency. The normal distribution is used to fit the slug frequency, and the predicted correlation is in good agreement with the experimental data.展开更多
The core-surface flow is crucial for understanding the dynamics of the Earth's outer core and geomagnetic secular variations.Conventional core flow models often use a single set of spherical harmonic coefficients ...The core-surface flow is crucial for understanding the dynamics of the Earth's outer core and geomagnetic secular variations.Conventional core flow models often use a single set of spherical harmonic coefficients to represent the flow both inside and outside the tangent cylinder,inherently imposing continuity across the tangent cylinder around the solid inner core.To address this limitation,we present a core-surface flow inversion framework based on physics-informed neural networks.This framework employs distinct neural network representations for the flow inside and outside the tangent cylinder,allowing for discontinuities as the flow crosses the tangent cylinder.Additionally,it incorporates secular acceleration data to constrain the temporal evolution of the core flow.Using this inversion framework,we derive a new core-surface flow model spanning 2001 to 2024 from a geomagnetic model,incorporating the latest magnetic data from Swarm satellites and Macao Science Satellite-1.The recovered model reveals persistent large-scale circulation linked to westward drift,significant temporal variations in the equatorial Pacific,and distinct jet-like structures at the poles.The inversion also reveals a large-scale wave pattern in equatorial azimuthal flow acceleration,corresponding to observed geomagnetic jerks and likely resulting from quasi-geostrophic magneto-Coriolis waves.Additionally,the framework infers small-scale magnetic fields at the core-mantle boundary,highlighting split flux concentrations and localized high-latitude patches.展开更多
The electromagnetic swirling flow in nozzle(EMSFN)technique is designed to mitigate the adverse effects of unstable and uneven flow within the submerged entry nozzle in continuous casting.Utilizing electromagnetic for...The electromagnetic swirling flow in nozzle(EMSFN)technique is designed to mitigate the adverse effects of unstable and uneven flow within the submerged entry nozzle in continuous casting.Utilizing electromagnetic forces,EMSFN stabilizes the flow within the nozzle,leading to a more controlled flow in the mold.Numerical simulations were used to quantitatively analyze the magnetic and flow fields in a slab continuous casting system under EMSFN.Results indicate that EMSFN significantly stabilizes the outflow from the nozzle,with stability increasing with higher current intensity.At 10,000 Ampere-turns(At)of the coil,meniscus fluctuations were unstable.They stabilized at 13,000 At,with minimal changes observed beyond this point.The optimal current intensity for stable mold flow,at a casting speed of 1.56 m/min,is 13,000 At.These findings confirm the effectiveness of EMSFN in stabilizing the internal flow field of the slab mold and determining optimal operational current intensity.展开更多
Accurate early classification of elephant flows(elephants)is important for network management and resource optimization.Elephant models,mainly based on the byte count of flows,can always achieve high accuracy,but not ...Accurate early classification of elephant flows(elephants)is important for network management and resource optimization.Elephant models,mainly based on the byte count of flows,can always achieve high accuracy,but not in a time-efficient manner.The time efficiency becomes even worse when the flows to be classified are sampled by flow entry timeout over Software-Defined Networks(SDNs)to achieve a better resource efficiency.This paper addresses this situation by combining co-training and Reinforcement Learning(RL)to enable a closed-loop classification approach that divides the entire classification process into episodes,each involving two elephant models.One predicts elephants and is retrained by a selection of flows automatically labeled online by the other.RL is used to formulate a reward function that estimates the values of the possible actions based on the current states of both models and further adjusts the ratio of flows to be labeled in each phase.Extensive evaluation based on real traffic traces shows that the proposed approach can stably predict elephants using the packets received in the first 10% of their lifetime with an accuracy of over 80%,and using only about 10% more control channel bandwidth than the baseline over the evolved SDNs.展开更多
Leesmidt et al present a comprehensive analysis of abdominal vascular flow in children using four-dimensional(4D)flow magnetic resonance imaging(MRI),aim to establish normal hemodynamic values for the abdominal viscer...Leesmidt et al present a comprehensive analysis of abdominal vascular flow in children using four-dimensional(4D)flow magnetic resonance imaging(MRI),aim to establish normal hemodynamic values for the abdominal visceral organs and to assess the feasibility of 4D flow MRI(4D-f-MRI)in this population.The researchers performed 4D-f-MRI on 9 pediatric patients with a history or suspi-cion of bowel pathology.Flow velocities were measured in the abdominal aorta and superior and inferior mesenteric arteries.The quality of the 4D-f-MRI images was evaluated,and the agreement between the measured flow velocities and those obtained from Duplex ultrasound was established.However,due to the specific limitations of this work,future studies should address the issues of small sample size and the specific age group design.展开更多
基金supported by the Major Project of the National Social Science Fund of China,titled“Design Path Selection for the Mechanism of New and Old Growth Driver Conversion”(Grant No.18ZDA077)by the Joint Special Major Research Project of the Yangtze River Delta Economics and Social Development Research Center at Nanjing University and the Collaborative Innovation Center for China Economy(CICCE),titled“Practicing Innovation in China’s Development Economics for the Yangtze River Delta:From Industrial Clusters to Technological Clusters”(Grant No.CYD2022006).
文摘The global clustering of inventive talent shapes innovation capacity and drives economic growth.For China,this process is especially crucial in sustaining its development momentum.This paper draws on data from the EPO Worldwide Patent Statistical Database(PATSTAT)to extract global inventive talent mobility information and analyzes the spatial structural evolution of the global inventive talent flow network.The study finds that this network is undergoing a multi-polar transformation,characterized by the rising importance of a few central countries-such as the United States,Germany,and China-and the increasing marginalization of many peripheral countries.In response to this typical phenomenon,the paper constructs an endogenous migration model and conducts empirical testing using the Temporal Exponential Random Graph Model(TERGM).The results reveal several endogenous mechanisms driving global inventive talent flows,including reciprocity,path dependence,convergence effects,transitivity,and cyclic structures,all of which contribute to the network’s multi-polar trend.In addition,differences in regional industrial structures significantly influence talent mobility choices and are a decisive factor in the formation of poles within the multi-polar landscape.Based on these findings,it is suggested that efforts be made to foster two-way channels for talent exchange between China and other global innovation hubs,in order to enhance international collaboration and knowledge flow.We should aim to reduce the migration costs and institutional barriers faced by R&D personnel,thereby encouraging greater mobility of high-skilled talent.Furthermore,the government is advised to strategically leverage regional strengths in high-tech industries as a lever to capture competitive advantages in emerging technologies and products,ultimately strengthening the country’s position in the global innovation landscape.
基金Under the auspices of National Natural Science Foundation of China(No.41001070,40801054,40371030)
文摘Theoretic and practical significance has been highlighted in the research of the roles and functions of destinations,as destinations are restricted by the spatial structure based on tourist flow network from the perspective of relationship.This article conducted an empirical analysis for Tourism Region of South Anhui(TRSA) and revealed the necessity and feasibility of studying the roles and functions of destinations from tourist flow network's perspective.The automorphic equivalence analysis and centrality analysis were used to classify 16 destinations in TRSA into six role types:tourist flow distribution center,hub of tourist flows,passageway destination,common touring destination,attached touring destination,and nearly isolated destination.Some suggestions were given on suitable infrastructure construction and destinations service designs according to their functions in network.This destination role positioning was based on tourist flow network structure in integral and macroscopic way.It provided an important reference for the balanced and harmonious development of all the destinations of TRSA.In addition,this article verified the applicability of social network analysis on tourist flow research in local scale,and expanded this method to destination role and function positioning.
文摘Computer networks and power transmission networks are treated as capacitated flow networks.A capacitated flow network may partially fail due to maintenance.Therefore,the capacity of each edge should be optimally assigned to face critical situations-i.e.,to keep the network functioning normally in the case of failure at one or more edges.The robust design problem(RDP)in a capacitated flow network is to search for the minimum capacity assignment of each edge such that the network still survived even under the edge’s failure.The RDP is known as NP-hard.Thus,capacity assignment problem subject to system reliability and total capacity constraints is studied in this paper.The problem is formulated mathematically,and a genetic algorithm is proposed to determine the optimal solution.The optimal solution found by the proposed algorithm is characterized by maximum reliability and minimum total capacity.Some numerical examples are presented to illustrate the efficiency of the proposed approach.
基金This project (No. 49070196) is funded by the National Science Foundation of China.
文摘In a large area of the east—central Asian continent there is a unified seismic network system composed of two families of large—seismic belts that intersect conjugately. Such a seismic network in the middle—upper crust is actually a response to the plastic flow network in the lower lithosphere including the lower crust and lithospheric mantle. The existence of the unified plastic flow system confirms that the driving force for intraplate tectonic deformation results mainly from the compression of the India plate, while the long-range transmission of the force is carried out chiefly by means of plastic flow. The plastic flow network has a control over the intraplate tectonic deformation.
文摘Based on the heat flow data published in 1990 and 2001, a study of the factors influencing the terrestrial heat flow distribution in the China continent and its quantitative expression is carried out using the ＂Netlike Plastic-Flow＂ continental dynamics model and the methods of statistic analysis and optimum fitting. The result indicates that the factors influencing the heat flow distribution is classified into two groups, i.e. background and tectonic ones, in which the former mainly involves the non- uniform distribution of mantle heat flow, heat production of radioactive dements in the crust, heattransfer media and hydrothermal circulation, while the latter mainly involves plastic-flow networks and relatively-stable blocks. The plastic-flow network is a manifestation of shear localization in the netlike plastic-flow process in the lower lithosphere, which is composed of two sets of plastic-flow belts （PFBs） intersecting each other and, as one of the basic action regimes, controls the intraplate tectonic deformation. Relatively stable blocks （RSBs）, which are the tectonic units with relatively-high viscosities existing in the netlike plastic-flow field, as one of the principal origins, result in the development of large-seale compressional basins. PFB and RSB, as the active and quiet states of tectonic deformation, give rise to the higher and lower heat flow values, respectivdy. The provincial average heat flow in continent can be estimated using the expression qav = q0 ＋ a Pbt-c Pbk, where the three terms of the right side are background heat flow, PFB-positive contribution and RSB-negative contribution, Pbt and Pbk are the PFB- and RSB-coverage ratios, respectively, a is the coefficient of PFB- positive contribution depending mainly on the strain in the lower lithosphere, and c is the coefficient of RSB-negative contribution related mainly to the thickness of the lithosphere, the aseismic-area ratio and the tectonic age. For the major portion of the China continent excluding some of the southeastern region of China, the confidence interval of the provincial average background heat flow is qo=57.25±24.8 mW/m^2 and the PFB-positive- and RSB-negative-contribution coefficients are a=14.8-71.9 mW/m^2 and c=0-25.6 mW/m^2, respectively. The concepts of PFB and RSB effects and the heat flow expression suggested provide a new choice of the approach to the quantitative description of the characteristics of heat flow distribution in continent and their physical mechanisms.
文摘Multipe NSSS (Nuclear Steam Supply System) modules use the common feeding-water system to drive the common turbine power generation set. The SSFFN (secondary side fluid flow network) of MHTGR plant has features i.e. strong-coupling and nonlinearity. A wide range of power switching operation will cause unsteady flow, which may destroy the working elements and will be a threat for normal operation. To overcome those problems, a differential-algebraic model and PI controllers are designed for the SSFFN. In MATLAB\SIMULINK environment, a simulation platform is established and used to make a simulation of SSFFN of a MHTGR plant with two NSSS modules, which uses feedwater valves to control the mass flow rate in each module instead of feedwater pump. Results reflect good robustness of controllers.
文摘Several conclusions on minimal cutset are proposed, from which a new algorithm is deduced to evaluate the unreliability of flow networks. Beginning with one unreliability product of the network, disjointed unreliability products are branched out one by one, every of which is selected from the network minimal cutsets. Finally the unreliability of the network is obtained by adding all these unreliability products up.
基金supported in part by the National Natural Science Foundation of China under Grant 72264036in part by the West Light Foundation of The Chinese Academy of Sciences under Grant 2020-XBQNXZ-020+1 种基金Social Science Foundation of Xinjiang under Grant 2023BGL077the Research Program for High-level Talent Program of Xinjiang University of Finance and Economics 2022XGC041,2022XGC042.
文摘Purpose:This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model(IKM).The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks.Design/Methodology/Approach:The IKM model enhances the preferential attachment and growth observed in scale-free BA networks,while incorporating three adjustment parameters to simulate the selection of connection targets and the types of nodes involved in the network evolution process Using the PageRank algorithm to calculate the significance of nodes within the knowledge flow network.To compare its performance,the BA and DMS models are also employed for simulating the network.Pearson coefficient analysis is conducted on the simulated networks generated by the IKM,BA and DMS models,as well as on the actual network.Findings:The research findings demonstrate that the IKM model outperforms the BA and DMS models in replicating the institutional field knowledge flow network.It provides comprehensive insights into the evolution mechanism of knowledge flow networks in the scientific research realm.The model also exhibits potential applicability to other knowledge networks that involve knowledge organizations as node units.Research Limitations:This study has some limitations.Firstly,it primarily focuses on the evolution of knowledge flow networks within the field of physics,neglecting other fields.Additionally,the analysis is based on a specific set of data,which may limit the generalizability of the findings.Future research could address these limitations by exploring knowledge flow networks in diverse fields and utilizing broader datasets.Practical Implications:The proposed IKM model offers practical implications for the construction and analysis of knowledge flow networks within institutions.It provides a valuable tool for understanding and managing knowledge exchange between knowledge organizations.The model can aid in optimizing knowledge flow and enhancing collaboration within organizations.Originality/value:This research highlights the significance of meso-level studies in understanding knowledge organization and its impact on knowledge flow networks.The IKM model demonstrates its effectiveness in replicating institutional field knowledge flow networks and offers practical implications for knowledge management in institutions.Moreover,the model has the potential to be applied to other knowledge networks,which are formed by knowledge organizations as node units.
文摘In the present paper, a three-component, stationary, multistate flow network system is studied. Detailed costs and incomes are specified. The aim is to minimize the expected total net loss with respect to the expected times the components spend in each state. This represents a novelty in that we connect the expected component times spent in each state to the minimal total net loss of the system, without first finding the component importance. This is of interest in the design phase where one may tune the components to minimize the expected total net loss. Due to the complex nature of the problem, we first study a simplified version. There the expected times spent in each state are assumed equal for each component. Then a modified version of the full model is presented. The optimization in this model is completed in two steps. First the optimization is carried out for a set of pre-chosen fixed expected life cycle lengths. Then the overall minimum is identified by varying these expectations. Both the simplified and the modified optimization problems are nonlinear. The setup used in this article is such that it can easily be modified to represent other flow network systems and cost functions. The challenge lies in the optimization of real life systems.
基金supported in part by the National Key RD Program of China (2021YFF0602104-2,2020YFB1804604)in part by the 2020 Industrial Internet Innovation and Development Project from Ministry of Industry and Information Technology of Chinain part by the Fundamental Research Fund for the Central Universities (30918012204,30920041112).
文摘The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology.Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis.Semantic segmentation is also a challenging technology for image understanding and scene parsing.We focused on the challenging task of real-time semantic segmentation in this paper.In this paper,we proposed a novel fast architecture for real-time semantic segmentation named DuFNet.Starting from the existing work of Bilateral Segmentation Network(BiSeNet),DuFNet proposes a novel Semantic Information Flow(SIF)structure for context information and a novel Fringe Information Flow(FIF)structure for spatial information.We also proposed two kinds of SIF with cascaded and paralleled structures,respectively.The SIF encodes the input stage by stage in the ResNet18 backbone and provides context information for the feature fusionmodule.Features from previous stages usually contain rich low-level details but high-level semantics for later stages.Themultiple convolutions embed in Parallel SIF aggregate the corresponding features among different stages and generate a powerful global context representation with less computational cost.The FIF consists of a pooling layer and an upsampling operator followed by projection convolution layer.The concise component provides more spatial details for the network.Compared with BiSeNet,our work achieved faster speed and comparable performance with 72.34%mIoU accuracy and 78 FPS on Cityscapes Dataset based on the ResNet18 backbone.
基金supported by the National Science and Technology Major Project of China(Grant No.2024ZD 1004302)the Key Scientific and Technological Research project of SINOPEC(Grant No.P25186).
文摘To clarify fluid flow mechanisms and establish effective development conditions in continental shale oil reservoirs,a high-temperature,high-pressure steady-state flow system integrated with nuclear magnetic resonance(NMR)technology has been developed.The apparatus combines sample evacuation,rapid pressurization and saturation,and controlled displacement,enabling systematic investigation of single-phase shale oil flow under representative reservoir conditions.Related experiments allow proper quantification of the activation thresholds and relative contributions of different pore types to flow.A movable fluid index(MFI),defined using dual T_(2) cutoff values,is introduced accordingly and linked to key flow parameters.The results reveal distinct multi-scale characteristics of single-phase shale oil transport,namely micro-scale graded displacement and macro-scale segmented nonlinear behavior.As the injection-production pressure difference increases,flow pathways are activated progressively,beginning with fractures,followed by large and then smaller macropores,leading to a pronounced enhancement in apparent permeability.Although mesopores and micropores contribute little to direct flow,their indirect influence becomes increasingly important,and apparent permeability gradually approaches a stable limit at higher pressure difference.It is also shown that the MFI exhibits a strong negative correlation with the starting pressure gradient and a positive correlation with apparent permeability,providing a rapid and reliable indicator of shale oil flow capacity.Samples containing through-going fractures display consistently higher MFI values and superior flowability compared with those dominated by laminated fractures,highlighting the pivotal role of well-connected fracture networks generated by large-scale hydraulic fracturing in improving shale oil production.
文摘This study investigates the enhancement of convective heat transfer in a serpentine pipe using ferrofluid flow influenced by dual non-uniform magnetic sources.The primary objective is to improve thermal performance in compact cooling systems,such as those used in heat exchangers.A two-dimensional,steady-state Computational Fluid Dynamic(CFD)model is developed in ANSYS Fluent to simulate the behavior of an incompressible ferrofluid under applied constant heat flux and magnetic fields.The magnetic force is modeled using the Kelvin force,which acts on magnetized nanoparticles in response to spatially varying electromagnetic fields generated by two strategically positioned current-carrying wires.The effects of magnetic field strength,quantified by the magnetic number(Mn),on flow behavior and temperature distribution are thoroughly analyzed.The results indicate that increasing Mn leads to higher Nusselt numbers,demonstrating enhanced convective heat transfer.Secondary vortices induced by magnetic forcing improve fluid mixing,particularly in curved regions of the pipe.A mesh-independence study and model validation with benchmark data support the reliability of the numerical framework.This work highlights the potential of magnetic-field-assisted thermal control in energy-efficient cooling applications and provides a foundation for the further development of advanced ferrofluid-based heat transfer systems.
基金funded by King Saud University,Riyadh,Saudi Arabia,through the Ongo-ing Research Funding program—Research Chairs(ORF-RC-2025-0127)funded via Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R443).
文摘The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates.This problem is important because it helps us understand the complicated connections between magnetic fields,nanofluid dynamics,and heat transport,all of which are critical for designing thermal management systems.These findings are especially useful for improving the design of innovative cooling technologies in electronics,energy systems,and healthcare applications.No prior study has been done on the theoretical study of the flow of ternary nanofluid(SiO_(2)+ZnO+MWCNT/Water−EthylGl ycol,(60∶40))past a pierced squeezed Riga plates using the boundary value problem solver 4th-order collocation(BVP4C)numerical approach to date.So,the current work has been carried out to fill this gap,and the core purpose of this study is to explore the aspects that enhance the heat transfer of base fluids(H_(2)O/EG)suspended with three nanomaterials SiO_(2),ZnO,and MWCNT.The Riga plates introduce electromagnetic forcing through an embedded array of magnets and electrodes,generating Lorentz forces to regulate the flow.The squeezing effect introduces dynamic boundary movement,which enhances mixing;however,permeability,due to porosity,replicates the true material limits.Similarity transformations of the Navier-Stokes and energy equations result in a highly nonlinear set of ordinary differential equations that govern momentum and thermal energy transport.The subsequent boundary value problem is solved utilizing the BVP4C numerical approach.The study observes the impact of magnetic parameters,squeezing velocity,solid volume percentages of the three nanoparticles,and porous medium factors on velocity and temperature fields.Results show that magnetic fields reduce the velocity profile by 6.75%due to increased squeezing and medium effects.Tri-hybrid nanofluids notice a 9%rise in temperature with higher thermal radiation.
基金supported by the funds from the National Natural Science Foundation of China(42041005 and 32101313)the CAS Strategic Priority Research Programme(A)(XDA20050103)Science&Technology Fundamental Resources Investigation Program(2022FY100100)。
文摘The escalating ecological consequences of state transitions have attracted significant attention in both theoretical and experimental studies,with a focus on determining the stable or equilibrium points of dynamic systems[1-5].Identifying equilibrium states not only reveals a system's current status but also offers insights into its evolutionary trajectory under specific environmental conditions[6].
基金The Key Project of National Natural Science Foundation of China(42130510)。
文摘Taking Shanghai as an example,this study obtained the online travel notes data from Xiaohongshu and Qunar in the past 10 years to construct the Shanghai tourist flow network(STFN)and used the methods of change point detection(CPD)and complex network analysis(CNA)to reveal the spatial structure characteristics of Shanghai tourism flow and the dynamic evolution process of STFN.The results showed that:(1)In the past 10 years,Shanghai tourist market had experienced a process of evolution from stable and orderly to short-term fluc-tuation and then gradual recovery,and the year of 2019 was the turning point of tourist flow network evolution.(2)The small-world and approximate scale-free characteristics of STFN were verified,and the network changed from disassortative to temporary assortative,showing a development trend of external expansion and internal separation.(3)While the centrality indicators of tourist flow network remained stable as a whole,the attention to cultural nodes was also increasing with the emergence of new nodes;(4)In terms of spatial connection,new popular nodes emerged and the relationship between them and the surrounding nodes was strengthened;(5)The spatial pattern of tourist flow network presented an inverted“V”shape and gradually expanded to southwest and southeast,forming a network with core nodes as the center and radiating outward.At the same time,newly emerging nodes at the periphery had formed relatively independent clusters.
基金supported by the Basic Science Center Program for Ordered Energy Conversion of the National Natural Science Foundation of China(No.52488201)the National Natural Science Foundation of China(No.52422606).
文摘Hilly terrain pipeline is a common form of pipeline in oil and gas storage and transportation industry.Due to the hilly terrain influence, the liquid at the elbow of the gathering pipeline is easy to flow back and accumulate to form slug flow, so it is necessary to remove the accumulated liquid by gas purging. In this paper, experiment is carried out in hilly terrain pipelines. Three flow patterns of stratified flow, slug flow and stratified entrained flow are observed. The process of gas purging accumulated liquid is divided into four stages, namely liquid accumulation, liquid rising, continuous outflow and tail outflow. At the same time, the flow pattern maps of each stage are drawn. The pressure drop signal is analyzed in time domain and frequency domain, and the contour map of pressure drop distribution is drawn. It is found that the ratio of range to average value can well distinguish the occurrence range of each flow pattern.Based on visualization, the transition process of slug flow to stratified flow and stratified entrained flow is studied, and the transition boundary prediction model is established. An image processing method is proposed to convert the image signal into a similarity curve, and PSD analysis is performed to calculate the slug frequency. The normal distribution is used to fit the slug frequency, and the predicted correlation is in good agreement with the experimental data.
基金supported by the National Natural Science Foundation of China (12250012,42250101)the Macao Foundation。
文摘The core-surface flow is crucial for understanding the dynamics of the Earth's outer core and geomagnetic secular variations.Conventional core flow models often use a single set of spherical harmonic coefficients to represent the flow both inside and outside the tangent cylinder,inherently imposing continuity across the tangent cylinder around the solid inner core.To address this limitation,we present a core-surface flow inversion framework based on physics-informed neural networks.This framework employs distinct neural network representations for the flow inside and outside the tangent cylinder,allowing for discontinuities as the flow crosses the tangent cylinder.Additionally,it incorporates secular acceleration data to constrain the temporal evolution of the core flow.Using this inversion framework,we derive a new core-surface flow model spanning 2001 to 2024 from a geomagnetic model,incorporating the latest magnetic data from Swarm satellites and Macao Science Satellite-1.The recovered model reveals persistent large-scale circulation linked to westward drift,significant temporal variations in the equatorial Pacific,and distinct jet-like structures at the poles.The inversion also reveals a large-scale wave pattern in equatorial azimuthal flow acceleration,corresponding to observed geomagnetic jerks and likely resulting from quasi-geostrophic magneto-Coriolis waves.Additionally,the framework infers small-scale magnetic fields at the core-mantle boundary,highlighting split flux concentrations and localized high-latitude patches.
基金supported by the Application Technology of Automotive Steels(No.2021040300048)the National Natural Science Foundation of China(No.52304347)+2 种基金Hebei Provincial Natural Science Foundation(No.E2019501008),China Baowu Low Carbon Metallurgy Innovation Foundation(BWLCF202320)Natural Science Foundation of Liaoning Province(Nos.2023-MSBA-135 and 2023-BSBA-107)Fundamental Research Funds for the Central Universities(Nos.N2409008 and N2409006).
文摘The electromagnetic swirling flow in nozzle(EMSFN)technique is designed to mitigate the adverse effects of unstable and uneven flow within the submerged entry nozzle in continuous casting.Utilizing electromagnetic forces,EMSFN stabilizes the flow within the nozzle,leading to a more controlled flow in the mold.Numerical simulations were used to quantitatively analyze the magnetic and flow fields in a slab continuous casting system under EMSFN.Results indicate that EMSFN significantly stabilizes the outflow from the nozzle,with stability increasing with higher current intensity.At 10,000 Ampere-turns(At)of the coil,meniscus fluctuations were unstable.They stabilized at 13,000 At,with minimal changes observed beyond this point.The optimal current intensity for stable mold flow,at a casting speed of 1.56 m/min,is 13,000 At.These findings confirm the effectiveness of EMSFN in stabilizing the internal flow field of the slab mold and determining optimal operational current intensity.
基金supported by the National Natural Science Foundation of China(61962016)the Ministry of Science and Technology of China(G2022033002L)+1 种基金National Natural Science Foundation of Guangxi(2022JJA170057)Guangxi Education Department’s Project on Improving the Basic Research Ability of Young and Middleaged Teachers in Universities(2023ky0812,Research on Statistical Network Delay Predictions in Large-scale SDNs).
文摘Accurate early classification of elephant flows(elephants)is important for network management and resource optimization.Elephant models,mainly based on the byte count of flows,can always achieve high accuracy,but not in a time-efficient manner.The time efficiency becomes even worse when the flows to be classified are sampled by flow entry timeout over Software-Defined Networks(SDNs)to achieve a better resource efficiency.This paper addresses this situation by combining co-training and Reinforcement Learning(RL)to enable a closed-loop classification approach that divides the entire classification process into episodes,each involving two elephant models.One predicts elephants and is retrained by a selection of flows automatically labeled online by the other.RL is used to formulate a reward function that estimates the values of the possible actions based on the current states of both models and further adjusts the ratio of flows to be labeled in each phase.Extensive evaluation based on real traffic traces shows that the proposed approach can stably predict elephants using the packets received in the first 10% of their lifetime with an accuracy of over 80%,and using only about 10% more control channel bandwidth than the baseline over the evolved SDNs.
文摘Leesmidt et al present a comprehensive analysis of abdominal vascular flow in children using four-dimensional(4D)flow magnetic resonance imaging(MRI),aim to establish normal hemodynamic values for the abdominal visceral organs and to assess the feasibility of 4D flow MRI(4D-f-MRI)in this population.The researchers performed 4D-f-MRI on 9 pediatric patients with a history or suspi-cion of bowel pathology.Flow velocities were measured in the abdominal aorta and superior and inferior mesenteric arteries.The quality of the 4D-f-MRI images was evaluated,and the agreement between the measured flow velocities and those obtained from Duplex ultrasound was established.However,due to the specific limitations of this work,future studies should address the issues of small sample size and the specific age group design.
